The Belgium Research Lab plays a leading role in researching novel technologies for next generation networks. These include a.o. the inception of fast converging algorithms customized to the solving of large-scale mathematical optimization problems involving nonlinear coupling constraints, nonconvex composite objectives, etc. In order to enlarge the team of high-end experts engaged in this research work, we invite for internship positions in Network Optimization fundamentals and applications, i.e., network design, routing/traffic assignment, resource allocation, flow/resource scheduling, etc.
Goals
Together with the research & engineering team in advanced mathematical and computational optimization focused on network applications, you will contribute to either of the following tasks
- Develop methods and algorithms customized for network optimization problems involving nonlinear coupling constraints, nonconvex/nonlinear composite objective functions, etc.
- Evaluate numerically these network optimization algorithms on selected use cases with synthetic and/or real-life data sets.
- Experiement them as part of a mathematical solver framework for their automated execution
Skills and competences
- Network optimization including network design, routing/traffic assignment, resource allocation, flow/resource scheduling, etc.
- Optimization methods/algorithms (must) : mixed integer (non)linear programming and at least one of the following:
o Iterative methods: first order methods (linesearch methods, subspace methods, etc.), Gauss-Siedel, Jacobi, Newton-Raphson methods, etc., Primal-dual methods (Lagrangian methods, etc.), interior point methods
o Projective/proximal methods
o Combinatorial methods: polyhedral methods, branch-and-cut, etc.
- Programming skills (must) : Octave and either C/C++ or FORTRAN (knowledge of Julia programming is considered as a plus)
- Knowledge of solving frameworks : (MI)NLP (e.g. Gurobi, SCIP, Couenne/COIN-OR, SHOT/COIN-OR, Algencan, Bonmin, etc.), Subsolvers (e.g. MIP: CPlex, NLP: Ipopt, Conopt) is considered as a strong plus
Candidate profile
- if MSc thesis: the candidate must be following the last year of the curriculum in, e.g., Applied/ Numerical mathematics, Math/Mechanical engineering, Theoretical computer science, Computer science engineering. Detailed coordinates of MSc promotor and his/her academic affiliation must be provided in the CV application form.
- if studentship/internship: the candidate must either be last year of an MSc curriculum in one of these disciplines or have completed an MSc (in one of these disciplines). Copy of the MSc diploma/certificate shall be included in annex of the CV. The internship can also be considered as part of post-MSc graduation or PhD graduation program.
- Note well: candidate must have obtained their University degree from an academic institution of one of the EU country.
Application : please provide complete CV with both curriculum and practical experience, including elements that demonstrate
- Good programming skills (experimental code) in Octave and either C/C++ or Fortran
- Knowledge in the handling of optimization methods and algorithms
- Excellent English level proficiency (both oral and written)
